Check if a Black Friday deal is really a deal with AI

Paste a deal and your shopping list, and get a plain check of the real price, what to compare, and whether it fits your budget before you buy.

The problem

Black Friday ads are built to rush you. A "50% off" tag may be off a price nobody paid, the model may be a cheaper version made for the sale, and the return window may be short. It's easy to spend more than you planned on things you didn't need.

Step by step

1. 1Write your shopping list and the most you want to spend on each item before the sales start.
2. 2When you see a deal, copy the product name, model number, sale price, "was" price and the store's return policy.
3. 3Paste them into the prompt below to get a checklist: what to compare, questions about the model number and warranty, and how it fits your budget.
4. 4Look up the price history yourself with a price tracker and compare the same model number at two or three other stores.
5. 5Buy only what's on your list and under your limit, and save receipts and return dates in one place.

Copy-paste prompt

Help me decide whether this Black Friday deal is worth it. Product: [name and model number]. Sale price: [price] at [store]. "Was" price shown: [price]. Return policy: [paste]. Why I want it: [reason]. My budget for this: [amount]. My full shopping list and budget: [paste]. Give me: (1) what to check about this exact model, including whether it might be a cheaper sale-only version; (2) a short list of things to compare at other stores; (3) questions about warranty and returns; (4) a plain yes, no or wait recommendation based only on my budget and list. Don't make up prices or price history; tell me where to look them up.

Tips and watch-outs

• Compare the exact model number; sale-only models can look the same but have cheaper parts.
• AI can't see live prices or price history, so look those up yourself.
• Set your limit before the sale starts, and check the return window before you buy.

Review AI output before using it. Don’t paste confidential, customer or patient data into tools your company hasn’t approved.